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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Artificial intelligence in solid waste management in India: current status and future prospects.

Rajesh Singh Gurjar¹, Sudesh Kumar², Arindam Kuila³

¹Department of Automation, Banasthali Vidyapith, Rajasthan, 304022, India.

Environmental Monitoring and Assessment

|October 31, 2025

Summary

Artificial intelligence (AI) can revolutionize solid waste management (SWM) in India by enhancing efficiency and reducing environmental impact. This review explores AI applications for smarter waste handling and sustainable solutions.

Keywords:

Artificial intelligence Chemical analysis Cost analysis Life cycle assessment Solid waste management

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Area of Science:

Environmental Science
Computer Science
Engineering

Background:

Rapid economic growth in India has led to increased energy consumption and solid waste generation, causing significant environmental and health issues.
Effective solid waste management (SWM) is crucial for mitigating these adverse effects and promoting sustainable development.

Purpose of the Study:

To investigate the integration and impact of artificial intelligence (AI) in India's solid waste management (SWM) sector.
To assess AI's potential for improving operational efficiency, reducing costs, and minimizing environmental consequences in SWM.

Main Methods:

Review of recent AI technologies applied to waste segregation, route optimization, resource recovery, and recycling.
Analysis of machine learning, computer vision, and predictive analytics in SWM.
Examination of case studies from Indian cities implementing AI-based waste management solutions.
Critical discussion on the application of Life Cycle Assessment (LCA) for evaluating AI-based SWM systems' sustainability and financial viability.

Main Results:

AI technologies demonstrate significant potential in enhancing waste segregation, optimizing collection routes, and improving recycling rates.
Case studies illustrate successful implementation of AI in Indian cities, leading to more efficient waste management.
Life Cycle Assessment (LCA) provides a framework for evaluating the environmental and economic benefits of AI in SWM.

Conclusions:

AI offers a transformative potential for restructuring India's SWM strategies, paving the way for more sustainable and efficient waste handling.
The adoption of AI in SWM is essential for addressing the challenges posed by increasing waste generation and ensuring environmental protection.